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Interactive Learning of Heterogeneous Visual Concepts with Local Features

Abstract : In the context of computer-assisted plant identification we are facing challenging information retrieval problems because of the very high within-class variability and of the limited number of training examples. To address these problems, we suggest a new interactive learning approach that combines similarity-based retrieval and re-ranking by SVM using local feature distributions. This approach leads to improved sample selection, allowing to obtain better results.
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https://hal.archives-ouvertes.fr/hal-01126108
Contributor : Laboratoire Cedric <>
Submitted on : Friday, March 6, 2015 - 11:40:25 AM
Last modification on : Monday, September 7, 2020 - 12:10:03 PM

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  • HAL Id : hal-01126108, version 1

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Wajih Ouertani, Michel Crucianu, Nozha Boujemaa. Interactive Learning of Heterogeneous Visual Concepts with Local Features. ACM Multimedia 2010 (short paper), Nov 2010, Florence, Italy. pp.995-998. ⟨hal-01126108⟩

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